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Large deviations for the time of ruin

Published online by Cambridge University Press:  14 July 2016

Harri Nyrhinen*
Affiliation:
University of Helsinki
*
Postal address: Department of Mathematics, PO Box 4, FIN 00014, University of Helsinki, Finland. Email address: nyrhinen@helsinki.fi.

Abstract

Let {Yn | n=1,2,…} be a stochastic process and M a positive real number. Define the time of ruin by T = inf{n | Yn > M} (T = +∞ if YnM for n=1,2,…). We are interested in the ruin probabilities for large M. Define the family of measures {PM | M > 0} by PM(B) = P(T/MB) for B ∊ ℬ (ℬ = Borel sets of ℝ). We prove that for a wide class of processes {Yn}, the family {PM} satisfies a large deviations principle. The rate function will correspond to the approximation P(T/Mx) ≈ P(YxM/M ≈ 1) for x > 0. We apply the result to a simulation problem.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1999 

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Footnotes

Supported by the Research Grants Committee of the University of Helsinki.

References

De Acosta, A., Ney, P., and Nummelin, E. (1991). Large deviation lower bounds for general sequences of random variables. In Progress in Probability 28, eds. Durrett, R. and Kesten, H. Birkhäuser, Boston, pp. 215221.Google Scholar
Asmussen, S., and Rubinstein, R. Y. (1995). Steady state rare events simulation in queueing models and its complexity properties. In Probability and Stochastics Series, ed. Dshalalow, J. H. CRC, Boca Raton, FL, pp. 429461.Google Scholar
Bucklew, J. A., Ney, P., and Sadowsky, J. S. (1990). Monte Carlo simulation and large deviations for uniformly recurrent Markov chains. J. Appl. Prob. 27, 4459.Google Scholar
Collamore, J. F. (1998). First passage times of general sequences of random vectors: A large deviations approach. Stoch. Proc. Appl. 78, 97130.CrossRefGoogle Scholar
Daykin, C. D., Pentikäinen, T., and Pesonen, M. (1994). Practical Risk Theory for Actuaries. Chapman and Hall, London.Google Scholar
Dembo, A., and Zeitouni, O. (1993). Large Deviations Techniques and Applications. Jones and Bartlett, Boston, MA.Google Scholar
Ellis, R. S. (1984). Large deviations for a general class of random vectors. Ann. Prob. 12, 112.Google Scholar
Embrechts, P., Grandell, J., and Schmidli, H. (1993). Finite-time Lundberg inequalities in the Cox case. Scand. Actuarial J., 1741.Google Scholar
Furrer, H. J., and Schmidli, H. (1994). Exponential inequalities for ruin probabilities of risk processes perturbed by diffusion. Insurance: Math. Econ. 15, 2336.Google Scholar
Glynn, P. W., and Whitt, W. (1994). Large deviations behavior of counting processes and their inverses. Queueing Systems 17, 107128.Google Scholar
Grandell, J. (1991). Aspects of Risk Theory. Springer, Berlin.Google Scholar
Lalley, S. P. (1984). Limit theorems for first-passage times in linear and non-linear renewal theory. Adv. Appl. Prob. 16, 766803.Google Scholar
Lehtonen, T., and Nyrhinen, H. (1992). Simulating level-crossing probabilities by importance sampling. Adv. Appl. Prob. 24, 858874.Google Scholar
Lehtonen, T., and Nyrhinen, H. (1992). On asymptotically efficient simulation of ruin probabilities in a Markovian environment. Scand. Actuarial J., 6075.Google Scholar
Martin-Löf, A. (1983). Entropy estimates for ruin probabilities. In Probability and Mathematical Statistics, eds. Gut, A. and Holst, L. Dept of Mathematics, Uppsala University, pp. 129139.Google Scholar
Martin-Löf, A. (1986). Entropy, a useful concept in risk theory. Scand. Actuarial J., 223235.Google Scholar
Nagell, T. (1951). Introduction to Number Theory. Wiley, New York.Google Scholar
Nummelin, E. (1994). Large deviations for functionals of stationary processes. Prob. Theory Rel. Fields 86, 387401.Google Scholar
Nyrhinen, H. (1995). On the typical level crossing time and path. Stoch. Proc. Appl. 58, 121137.Google Scholar
Nyrhinen, H. (1998). Rough descriptions of ruin for a general class of surplus processes. Adv. Appl. Prob. 30, 10081026.Google Scholar
O'Brien, G. L., and Vervaat, W. (1995). Compactness in the theory of large deviations. Stoch. Proc. Appl. 57, 110.Google Scholar
Puhalskii, A., and Whitt, W. (1997). Functional large deviation principles for first-passage-time processes. Ann. Appl. Prob. 7, 362381.Google Scholar
Rockafellar, R. T. (1970). Convex Analysis. Princeton University Press, Princeton, NJ.CrossRefGoogle Scholar
Sadowsky, J. S. (1996). On Monte Carlo estimation of large deviations probabilities. Ann. Appl. Prob. 6, 399422.Google Scholar
Schmidli, H. (1995). Cramér–Lundberg approximations for ruin probabilities of risk processes perturbed by diffusion. Insurance: Math. Econ. 16, 135149.Google Scholar
Schmidli, H. (1996). Lundberg inequalities for a Cox model with a piecewise constant intensity. J. Appl. Prob. 33, 196210.Google Scholar
Tiefeng, J. (1994). Large deviations for renewal processes. Stoch. Proc. Appl. 50, 5771.Google Scholar